【课程内容】
第一周：数据剖析思想
1.数据剖析的道与术
2.数据剖析思想结构化公式化流程化
3.剖析思想技巧象限法比照法假设法二八法多维法指数法
4.像咨询参谋相同考虑
5.怎么在业余时间训练剖析思想
第二周：事务
1.为什么事务重要？
2.经典的事务剖析目标市场营销模型产品运营模型用户行为模型电子商务模型流量模型
3.事务的剖析结构怎么树立剖析结构？市场营销剖析结构产品运营剖析结构用户行为剖析结构电子商务剖析结构网站剖析结构怎么应对各类事务布景
4.数据化管理事务
第三周：Excel
1.Excel的新手须知
2.Excel函数清洗处理类相关匹配类逻辑运算类核算核算类时间序列类
3.Excel东西数据透视表条件格局和迷你图自定义称号数组数据剖析库切片
4.用Excel进行数据剖析
第四周：数据可视化
1.数据可视化的魅力
2.常见的图表类型与使用散点图折线图柱形图和直方图饼图面积图雷达图漏斗图
3.高档图表类型与使用树型图桑基图热力求相关图箱线图标靶图词云图地理图
4.图表制作基础图表制作的关键高档图表制作辅助线复合图表好用的第三方图表库图表和报表
5.可视化BIPower BI入门导入数据表DataX数据收拾和相关可视化Dashboard第三方图库
6.用BI进行数据剖析
第五周：MySQL
1.数据库基础MySQL装置数据库和表数据类型
2.MySQL语法查询过滤高档过滤分组和聚合子查询核算函数表联合高档表联合
3.MySQL进阶优化高档技巧Leetcode比赛
4.用MySQL进行数据剖析
第六周：核算学
1.描绘核算学集中量数权重预估数据散布用Excel进行核算学
2.数据剖析的概率概率的国际概率散布假设检验AB测验方差剖析
3.时间序列
4.为什么会被核算学诈骗？
5.数据剖析与机器学习
第七周：Python
1.为什么要学习Python
2.Python的数据科学环境
3.Python的基础语法结构数据架构函数和类高档函数常用的数据剖析包事例操练
4.Numpy和PandasNumpy的数据结构Numpy的基础操作Numpy的函数Pandas的数据结构Pandas的基础操作Pandas的函数Pandas的数据规整功率技巧聚合时间序列
5.用Python进行数据剖析事例：数据剖析师的薪资事例：电商用户消费行为
6.可视化Matplotlibseaborn其他
7.构建数据剖析渠道Python衔接数据库Python进行ETL
如遇到链接失效请提交工单处理。
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